Adaptive Square-Diamond Search(ASDS) Algorithm for Fast Block Matching Motion Estimation

This paper presents an efficient search algorithm for fast block matching motion estimation(ME) for video applications. The algorithm uses two patterns for initial search and refined local search. For initial search, the proposed algorithm uses a square pattern adaptively by selecting the step size based on Maximum Absolute Value of predicted motion vector. This search pattern is aimed to reduce the computational complexity of the ME block and find the least error. If the least error point is in the middle of the pattern, it shows that image is still and terminates the search. If the least error point is other than the middle point, then it becomes a new origin for subsequent refined local search with the pattern as small diamond. This is iteratively continued until the final motion vector is found. The efficacy of the proposed algorithm is verified by comparing with existing search algorithms in terms of PSNR, computations/search points and elapsed time for motion estimation. Simulation results when compared with Exhaustive Search(ES) algorithm show that the proposed algorithm reduces number of search points by 96%. The PSNR performance is close to the ES search method by 99.8% and the elapsed time saving is 95%. This savings ensure that the proposed algorithm is suited for real-time applications. Keywords— Motion estimation, Search algorithm, Square pattern, Small Diamond, Block matching.